What term refers to the raw information used to train, validate, and test machine learning models?

What term refers to the raw information used to train, validate, and test machine learning models?

• A. Data
• B. Data cleaning
• C. Tool creation
• D. Data visualization

Answer: (A)

Data is the raw information used to train, validate, and test machine learning models. It encompasses the examples you feed into the model, often organized as features and, for supervised tasks, labels. This material is typically split into training data (to teach the model), validation data (to tune choices like model type and hyperparameters), and test data (to assess final performance on unseen information). Cleaning the data is a preprocessing step to fix errors or handle missing values, not the material itself. Visualization helps you explore the data to understand distributions and relationships, but it isn’t the data used for training the model.

Data is the raw information used to train, validate, and test machine learning models. It encompasses the examples you feed into the model, often organized as features and, for supervised tasks, labels. This material is typically split into training data (to teach the model), validation data (to tune choices like model type and hyperparameters), and test data (to assess final performance on unseen information). Cleaning the data is a preprocessing step to fix errors or handle missing values, not the material itself. Visualization helps you explore the data to understand distributions and relationships, but it isn’t the data used for training the model.